Occupancy detection is an important component in the automated video analytics field. In video based on-street applications, cameras are often installed to monitor vehicles. One application for such cameras is to monitor High Occupancy Vehicle (HOV) highway lanes. HOV lanes require a minimum number of passengers riding in the vehicle in order to be eligible to use the lane. More recently High Occupancy Tolling (HOT) applications have been developed. HOT lanes determine the toll amount according to the number of occupants in the vehicle. HOV/HOT lane requirements are used as a means for reducing congestion in high traffic locations. The fee associated with using HOV/HOT lanes can be adjusted to preserve vehicle speed in the lane.
It has been observed that violation rates of occupancy requirements associated with HOV and HOT lanes are often significant. The current method for HOV/HOT enforcement is limited to visual inspection performed by police officers at roadside. Visual inspection has a number of drawbacks; it is expensive, difficult, and generally ineffective. Published studies indicate that less than 10% of HOV violators are caught and ticketed through visual enforcement. It is dangerous for police officers to pursue HOV/HOT violators at high speed in congested highway traffic. Furthermore, visual inspection can be compromised by inclement weather. Therefore, a need exists for automated enforcement methods and systems.